ON-THE-GO TOUCHLESS FINGERPRINT SCANNER

• US 20150227774A1
• Filed: 02/12/2015
• Published: 08/13/2015
• Est. Priority Date: 02/12/2014
• Status: Active Grant

• Current Assignee: Zeroconzero LLC
• Original Assignee: Advanced Optical Systems
• Inventors: Balch, Michael Kevin, Fox, Stephen Harris, Hartman, Richard Leon, Rosetti, Nicholas Clark
• Granted Patent: US 9,489,560 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06V 40/11 Hand-related biometrics; Hand pose recognition
• CPC Class Codes: G06V 40/1312 direct reading, e.g. contactless acquisition
• CPC Class Codes: G06V 40/1365 Matching; Classification

Abstract

On-the-go fingerprint scanners and methods of capturing fingerprints on-the-go are disclosed. In some aspects, the on-the-go fingerprint scanner can include a scanning area and a beam break sensor disposed coincident to the scanning area such that the beam break sensor detects when an object passes through the scanning area. The scanner can also include at least one hand camera configured to capture a video image of the scanning area such that when the beam break sensor detects that an object has passed through the scanning area, the hand camera detects whether the object is a human hand and the location of any fingers on said hand, and at least one fingerprint camera configured to receive the location of any fingers within the scanning area from the hand camera and capture a high-resolution image of at least a portion of any of said fingers passing through the scanning area.

Claims

1. An on-the-go fingerprint scanner, comprising:

a scanning area;

a beam break sensor disposed coincident to the scanning area such that the beam break sensor detects when an object passes through the scanning area;

at least one hand camera configured to capture an image of the scanning area such that when the beam break sensor detects that an object has passed through the scanning area, the hand camera detects whether the object is a human hand and a location of any fingers on said hand; and

at least one fingerprint camera configured to receive the location of any fingers within the scanning area from the hand camera and capture a high-resolution image of at least a portion of any of said fingers passing through the scanning area.

2. The fingerprint scanner of claim 1, further comprising:

an illumination system configured to illuminate an object passing through the scanner area, the illumination system having any of a high-power extended light source, a compound hyperbolic concentrator, a lens, a diffuser, or any combination thereof.

3. The fingerprint scanner of claim 2, wherein the illumination system further includes a baffle.

4. The fingerprint scanner of claim 1, wherein at least one of the scanning area and the beam break sensor further comprise a cueing light.

5. The fingerprint scanner of claim 1, wherein the at least one hand camera is disposed at least one meter from the scanning area.

6. The fingerprint scanner of claim 1, wherein the at least one fingerprint camera is disposed at least one meter from the scanning area.

7. The fingerprint scanner of claim 1, further comprising:

a controller having at least one processor, the controller being configured to send and receive data to each of the beam break sensor, the at least one hand camera, and the at least one fingerprint camera such that the controller coordinates the activity thereof.

8. The fingerprint scanner of claim 7, wherein the controller is configured to compare data received from any of the at least one hand camera and the at least one fingerprint camera to at least one of a neural network, an Active Shape Model, or a database containing known fingerprint or other biometric data.

9. An on-the-go fingerprint scanner, comprising:

a scanning area;

a beam break sensor disposed coincident to the scanning area such that the beam break sensor detects when an object passes through the scanning area;

at least one hand camera configured to capture a video image of the scanning area such that when the beam break sensor detects that an object has passed through the scanning area, the hand camera;

acquires an image of the object,

detects whether the object is a human hand by determining a contour around the perimeter of the object, applying landmark points to the contour, and comparing the contour to a previously trained Active Shape Model of a hand,

detects a location of any fingers on said detected hand by processing the location of the landmark points, and

detects the presence or absence of any fingers using a neural network; and

at least one fingerprint camera configured to receive the location of any fingers within the scanning area from the hand camera and capture a plurality of high-resolution images of at least a portion of any of said fingers passing through the scanning area.

10. The fingerprint scanner of claim 9, wherein the hand camera acquires an image of the object by acquiring a last frame from the hand camera video image after the beam brake sensor detects the presence of the object.

11. The fingerprint scanner of claim 9, wherein the fingerprint scanner is configured to determine a focus metric for each of the plurality of high-resolution images and retain those images with the highest focus metric for further processing.

12. The fingerprint scanner of claim 9, wherein at least one of the plurality of high-resolution images is further processed by at least one of:

downsampling the image to 500 PPI, performing a full-frame brightness correction, applying a ridge detection algorithm, processing for both binary and grey level output, or any combination thereof.

13. The fingerprint scanner of claim 9, further comprising:

an illumination system configured to illuminate an object passing through the scanner area, the illumination system having any of a high-power extended light source, a compound hyperbolic concentrator, a lens, a diffuser, or any combination thereof.

14. The fingerprint scanner of claim 13, wherein the illumination system further includes a baffle.

15. A method of capturing a fingerprint on-the-go, comprising:

determining that an object is passing through a predefined scanning area;

acquiring an image of the object and detecting whether the object is a human hand by determining a contour around the perimeter of the object, applying landmark points to the contour, and comparing the contour to a previously trained Active Shape Model of a hand;

detecting a location of any fingers on said detected hand by processing the location of the landmark points;

detecting the presence or absence of any fingers using a neural network; and

acquiring at least one high-resolution image of a tip portion of any detected finger.

16. The method of claim 15, further comprising:

comparing the at least one high-resolution image of the tip portion of any detected finger against a database of biometric information.

17. The method of claim 15, further comprising:

storing the at least one high-resolution image of the tip portion of any detected finger in a database of biometric information.

18. The method of claim 15, further comprising:

determining a focus metric for each of the at least one high-resolution images.

19. The method of claim 18, further comprising:

retaining those images with the highest focus metric for further processing.

20. The method of claim 15, further comprising:

processing the at least one high-resolution image by at least one of;

downsampling the image to 500 PPI, performing a full-frame brightness correction, applying a ridge detection algorithm, processing for both binary and grey level output, or any combination thereof.